Actual causality in fault trees
For reliability engineers and risk analysts, this work bridges fault tree analysis and causality theory, offering a formal foundation for failure diagnosis, though it is an incremental application of existing theory.
This paper applies Halpern & Pearl's theory of actual causality to fault trees, enabling failure diagnostics by answering 'why has it gone wrong?'. It provides a complete classification of actual causality notions in terms of fault tree structure and shows that minimal cut sets correspond to actual causes.
Fault trees are a widely used as effective risk models for complex systems, answering the question "what can go wrong?", especially through minimal cut set analysis. We study fault trees from the perspective of Halpern & Pearl's theory of actual causality. This allows us to use fault trees to answer the question "why has it gone wrong?", which is fundamental to failure diagnostics. We give a complete classification of each of the different notions of actual causality in terms of the fault tree's graph structure and logical structure, and show how minimal cut sets give rise to actual causes.